A user carries out a variety of behaviors during daily life, and many of these behaviors influence other people. Other users who have seen a certain user carrying out a behavior often carry out the same behavior. For example, there are cases in which another user who has seen a certain user cleaning when using a public place also cleans after using the same place. Conversely, there are also cases in which another user who has seen a certain user throwing away an empty can onto the street also throws away an empty can in the same manner. In this way, when another user who has seen the behavior of a certain user and has a connection with the user carries out a similar behavior, it is inferred that the behavior of the certain user has influenced the another user.
Furthermore, it is thought that the behavior of the certain user influences the another user not only when the another user has directly seen the certain user carrying out the behavior but also when the another user has seen the result of the behavior of the certain user. For example, there are cases in which a user who has seen a place that has been cleaned by the previous user also wants to maintain the cleanliness of that place, or there are cases in which a user who has seen that an empty can has been thrown away also throws away an empty can.
With regard to the example of an empty can, it has actually been reported as the result of a study that when somebody throws away an empty can in a place other than a specified place, there is an increase in cases where somebody else who next comes to that place similarly throws away an empty can in that place. This is said to be because the psychological resistance with respect to throwing away an empty can weakens as the degree to which a person feels that their action of throwing away an empty can worsens the environment decreases due to an empty can having already been thrown away (Non Patent Literature 1).
In this way, the everyday behavior of a user and the results thereof influence other users; yet, there are not many ways in which the user is able to realize this. In the abovementioned examples, the user did not know that another user has cleaned after the user had cleaned, and the user was not able to perceive that throwing away an empty can became the trigger for the similar behavior of another user. If the user knew that it is possible for his or her selfless behavior such as in the former example to induce the selfless behavior of another user, there is a possibility of the selfless behavior of the user being promoted. Conversely, if the user knew that his or her selfish behavior has become the trigger for the selfish behavior of another user, there is a possibility of the selfish behavior of the user being suppressed. In this way, the user knowing what kind of influence his or her behavior will possibly have on other users thereafter becomes a catalyst for changing the behavior of that user.
As an example of technology that notifies a user of what another person has thought upon seeing a behavior of the user or the result thereof after the user has carried out the behavior, in Patent Literature 1 for example, a system is proposed in which a user inputs an image of a behavior to be carried out by the user, the user writes the result of carrying out the behavior in a diary, and the user receives feedback in the form of comments from other users who have seen the diary. Furthermore, as an example of technology that predicts how the future will turn out if a user carries out behaviors in accordance with a schedule, in Patent Literature 2 for example, technology is proposed in which biometric data such as the brain waves and body temperature of the user and environment data such as air temperature and air pressure are analyzed in combination with a list of past behaviors, a comparison is made with the future schedule of the user, and advice is given as to what kind of health condition will be attained if the user carries out behaviors according to that schedule.
In Patent Literature 3, an electronic computer is presented which computes a social network configuration model that takes into account the influence that communication over the social network has on the consumption behavior of a consumer. In Patent Literature 4, a behavior prediction system is presented in which the present condition of a user is analyzed, and behavior candidates which are candidates for the next behavior of the user are generated on the basis of behavior history information. This behavior prediction system learns from user selection results or behavior results, and controls the generation of behavior candidates on the basis of the learning results and the present condition of the user.
In Patent Literature 5, a behavior promotion and suppression system is presented in which the behavior of a user is promoted by presenting information as to his or her (the user) position among all users, and information as to the present condition of other users (rivals) in the vicinity of the his or her position. In Patent Literature 6, a recognition device is presented which extracts a feature quantity indicating a change in the state of a subject, and uses a feature quantity database to automatically recognize the action or behavior indicated by the feature quantity.